In today's information-rich society, we encounter statistical information on a daily basis, ranging from unemployment rates, retail figures and cancer rates, to football ladders and cricket scores. Statistics tell interesting stories and enable us to make sense of the world. Statistics are essential for research, planning and decision-making purposes.

There are several concepts that recur throughout the literature on statistical literacy. These fall into four key areas and can be considered in a practical manner as ‘criteria’ on which to base statistical literacy:

Data awareness

The ability to understand statistical concepts

The ability to analyse, interpret and evaluate statistical information

The ability to communicate statistical information and understandings

In this issue, we will focus on understanding statistical concepts, and examine the difference between original, trend and seasonally adjusted data.

What is ‘Original Data’?

‘Original’ means that very little has been done to the data. It is raw data, straight from the survey and shows all the ups and downs of the data being measured. You can see that the original data in the graph shows there is a spike in retail sales in December each year. This is due to increased spending for Christmas.

What does ‘Seasonally Adjusted’ mean?

Seasonal adjustment allows for and removes the regular, reoccurring influences that could distort the short term view of what is happening. For example, retail sales figures are always larger in December due to Christmas so the spike in retail spending is smoothed out.
What is a ‘Trend Estimate’?

A trend estimate has not only had its seasonal factors allowed for, but it has also had effects from once-off, or irregular events, removed so that the data is not thrown off by what are essentially random events. For example, the Sydney Olympics distorted the ABS statistics on non-residential building approvals for that year. Trends are usually referred to in terms of direction e.g. whether the long term pattern of behaviour is showing an increase or a decrease.

What is a ‘Time Series’?

A time series is a set of regular observations on a subject and enables you to see how things have changed over time. Seasonally adjusted and trend data is most appropriate in relation to a set of time series data. A time series can be made up of economic data – such as monthly retail sales; demographic data like the population Census, or even social data comparing a household’s expenditure or people’s use of time between surveys.